code: def test_are_array_identical():
      arr1 = np.ones(4)
      orig1 = arr1.copy()
  
      arr2 = arr1
      orig2 = arr2.copy()
  
      assert are_arrays_identical(arr1, arr2)
      np.testing.assert_array_almost_equal(orig1, arr1, decimal=10)
      np.testing.assert_array_almost_equal(orig2, arr2, decimal=10)
  
      arr2 = arr1[:1]
      orig2 = arr2.copy()
      assert are_arrays_identical(arr1, arr2)
      np.testing.assert_array_almost_equal(orig1, arr1, decimal=10)
      np.testing.assert_array_almost_equal(orig2, arr2, decimal=10)
  
      arr2 = arr1[1:]
      orig2 = arr2.copy()
      assert not are_arrays_identical(arr1, arr2)
      np.testing.assert_array_almost_equal(orig1, arr1, decimal=10)
      np.testing.assert_array_almost_equal(orig2, arr2, decimal=10)
  
      arr2 = arr1.copy()
      orig2 = arr2.copy()
      assert not are_arrays_identical(arr1, arr2)
      np.testing.assert_array_almost_equal(orig1, arr1, decimal=10)
      np.testing.assert_array_almost_equal(orig2, arr2, decimal=10)
  
file_path: nilearn/nilearn/_utils/tests/test_numpy_conversions.py
imports: import os
  import tempfile
  import numpy
  import pytest
  from nilearn._utils.numpy_conversions import as_ndarray, csv_to_array
label_desc: Use image node_id 2 for calling a global function with example usage: test_are_array_identical() without return types